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      Bioinformatics approaches identified dasatinib and bortezomib inhibit the activity of MCM7 protein as a potential treatment against human cancer

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          Abstract

          Minichromosome Maintenance Complex Component 7 (MCM7) is a key component of the DNA replication licensing factor and hexamer MCM (MCM2–7) complex that regulates the DNA replication process. The MCM7 protein is associated with tumor cell proliferation that plays an important role in different human cancer progression. As the protein is highly expressed during the cancer development process, therefore, inhibition of the protein can be utilized as a treatment option for different human cancer. However, the study aimed to identify potential small molecular drug candidates against the MCM7 protein that can utilize treatment options for human cancer. Initially, the compounds identified from protein-drugs network analysis have been retrieved from NetworkAnalyst v3.0 server and screened through molecular docking, MM-GBSA, DFT, pharmacokinetics, toxicity, and molecular dynamics (MD) simulation approach. Two compounds namely Dasatinib (CID_3062316) and Bortezomib (CID_387447) have been identified throughout the screening process, which have the highest negative binding affinity (Kcal/mol) and binding free energy (Kcal/mol). The pharmacokinetics and toxicity analysis identified drug-like properties and no toxicity properties of the compounds, where 500 ns MD simulation confirmed structural stability of the two compounds to the targeted proteins. Therefore, we can conclude that the compounds dasatinib and bortezomib can inhibit the activity of the MCM7 and can be developed as a treatment option against human cancer.

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          Global cancer statistics 2020: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries

          This article provides an update on the global cancer burden using the GLOBOCAN 2020 estimates of cancer incidence and mortality produced by the International Agency for Research on Cancer. Worldwide, an estimated 19.3 million new cancer cases (18.1 million excluding nonmelanoma skin cancer) and almost 10.0 million cancer deaths (9.9 million excluding nonmelanoma skin cancer) occurred in 2020. Female breast cancer has surpassed lung cancer as the most commonly diagnosed cancer, with an estimated 2.3 million new cases (11.7%), followed by lung (11.4%), colorectal (10.0 %), prostate (7.3%), and stomach (5.6%) cancers. Lung cancer remained the leading cause of cancer death, with an estimated 1.8 million deaths (18%), followed by colorectal (9.4%), liver (8.3%), stomach (7.7%), and female breast (6.9%) cancers. Overall incidence was from 2-fold to 3-fold higher in transitioned versus transitioning countries for both sexes, whereas mortality varied <2-fold for men and little for women. Death rates for female breast and cervical cancers, however, were considerably higher in transitioning versus transitioned countries (15.0 vs 12.8 per 100,000 and 12.4 vs 5.2 per 100,000, respectively). The global cancer burden is expected to be 28.4 million cases in 2040, a 47% rise from 2020, with a larger increase in transitioning (64% to 95%) versus transitioned (32% to 56%) countries due to demographic changes, although this may be further exacerbated by increasing risk factors associated with globalization and a growing economy. Efforts to build a sustainable infrastructure for the dissemination of cancer prevention measures and provision of cancer care in transitioning countries is critical for global cancer control.
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            Cytoscape: a software environment for integrated models of biomolecular interaction networks.

            Cytoscape is an open source software project for integrating biomolecular interaction networks with high-throughput expression data and other molecular states into a unified conceptual framework. Although applicable to any system of molecular components and interactions, Cytoscape is most powerful when used in conjunction with large databases of protein-protein, protein-DNA, and genetic interactions that are increasingly available for humans and model organisms. Cytoscape's software Core provides basic functionality to layout and query the network; to visually integrate the network with expression profiles, phenotypes, and other molecular states; and to link the network to databases of functional annotations. The Core is extensible through a straightforward plug-in architecture, allowing rapid development of additional computational analyses and features. Several case studies of Cytoscape plug-ins are surveyed, including a search for interaction pathways correlating with changes in gene expression, a study of protein complexes involved in cellular recovery to DNA damage, inference of a combined physical/functional interaction network for Halobacterium, and an interface to detailed stochastic/kinetic gene regulatory models.
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              Development of the Colle-Salvetti correlation-energy formula into a functional of the electron density

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                Author and article information

                Contributors
                amdadbge@gmail.com
                ms.rahman@just.edu.bd
                Journal
                Sci Rep
                Sci Rep
                Scientific Reports
                Nature Publishing Group UK (London )
                2045-2322
                27 January 2022
                27 January 2022
                2022
                : 12
                : 1539
                Affiliations
                [1 ]Department of Genetic Engineering and Biotechnology, Jashore University of Science and Technology, Jashore, 7408 Bangladesh
                [2 ]Bioinformatics and Microbial Biotechnology Laboratory, Department of Genetic Engineering and Biotechnology, Jashore University of Science and Technology, Jashore, 7408 Bangladesh
                [3 ]GRID grid.254224.7, ISNI 0000 0001 0789 9563, Department of Food and Nutrition, College of Biotechnology and Natural Resource, , Chung-Ang University, ; Anseong, Gyeonggi-do 17546 Republic of Korea
                Article
                5621
                10.1038/s41598-022-05621-0
                8795118
                35087187
                9bcf8668-96cf-400b-a35c-6cfa76e5b251
                © The Author(s) 2022

                Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 23 July 2021
                : 14 January 2022
                Categories
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                Custom metadata
                © The Author(s) 2022

                Uncategorized
                virtual drug screening,cheminformatics,pharmacodynamics,pharmacokinetics
                Uncategorized
                virtual drug screening, cheminformatics, pharmacodynamics, pharmacokinetics

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